ANS:

Size: px
Start display at page:

Download "ANS:"

Transcription

1 Math 15-Spring 17-Final Exam Solutions 1. Consider the following definition of the symbol. Definition. Let x and y be integers. Write x y if 5x + 7y = 11k for some integer k. (a) Show that 1 4, 2 8, and = 11 3, = 11 6, and = 11 5 (b) Find a counterexample to the following statement: If a b and c d, then a c b d. 1 4 and 4 5, but 4 20, since = 160 is not a multiple of To prove a statement of the form ( x)(p (x) Q(x)), using contraposition, begin your proof with a sentence of the form Let x be [an element of the domain], and suppose Q(x). Then write a sequence of justified conclusions culminating in P (x). Use this method to prove the following: Let n be an integer. If n 2 + n + 1 is even, then n is odd. Let n Z and suppose n 2Z, then k Z n = 2k. This means that n 2 + n = (2k) 2 + 2k = 2(2k 2 + k) is even, so n 2 + n + 1 is odd. The odd thing about this proof, of course, is that n 2 + n + 1 is always odd! 3. Draw an undirected graph G with the following properties. The vertices of G correspond to the elements of the power set P ({0, 1, 2}). Two vertices (corresponding to A, B P ({0, 1, 2})) are connected by an edge if and only if A B =. {1, 2, 3} {2, 3} {1} {1, 3} {2} {1, 2} {3} 4. Construct addition and multiplication tables for Z/7. (only use equivalence class representatives in {0, 1, 2, 3, 4, 5, 6})

2 5. A partition of a positive integer n is a list of positive integers a 1, a 2,..., a k such that a 1 +a 2 + +a k = n. For example, the partitions of 5 are {5}, {1, 4}, {2, 3}, {1, 1, 3}, {1, 2, 2}, {1, 1, 1, 2}, {1, 1, 1, 1, 1}. The order of the list doesn t matter. There is a natural partial ordering on the set of partitions of n: if P 1 and P 2 are partitions, define P 1 P 2 if P 1 can be obtained by combining parts of P 2. For example, {1, 2, 2} {1, 1, 1, 1, 1} because {1, 2, 2} = {1, 1 + 1, 1 + 1}. On the other hand, {2, 3} and {1, 4} are incomparable elements in this poset. (a) Write the partitions of 6 in a Hasse diagram. (There are 11 partitions of 6.) (b) If a poset (X, ) has no incomparable elements, it is called a total ordering. For example, the real numbers R are totally ordered by the relation. Is the above ordering on the partitions of 6 a total ordering? Why or why not? No. There are incomparable elements, (e.g., 3,3 and 2,2,2). 6. The complete bipartite graph K m,n is the simple undirected graph with m + n vertices split into two sets V 1 and V 2 ( V 1 = m, V 2 = n) such that vertices x, y share an edge if and only if x V 1 and y V 2. (a) Draw K 3,3. How many edges does it have? l 1 r 1 l 2 r 2 l 3 r 3 K 3,3 has 9 edges. (b) How many edges does K n,n have? How do you know? Since forming an edge means choosing 1 of the vertices on the left and 1 of the vertices on Page 2

3 the right, and there are n choices for each, the number of edges is n n = n 2. (c) Let E(n) be the number of edges in K n,n. Clearly, E(1) = 1. Write E(n) in terms of E(n 1) for n > 1. E(n) = E(n 1) + 2n 1 For instance, E(3) = E(2) + 5 = Analyze the sequence 2, 7, 34, 91, 190 using sequences of differences. (a) From what degree polynomial does this sequence appear to be drawn? (Don t bother finding the coefficients of the polynomial.) p(x) Evidently, the third-order difference are the same, so the polynomial is cubic. (b) What would the next number in the sequence be? Given that the third order difference of the next term will be 12, the second order difference would be 54, the first order difference would be 153 and p(x next ) = Define a set X of numbers as follows. B. 5 X. R 1. If x X, so is 3x. R 2. If x X, so is x + 6. (a) List, in order, all the elements of X that are less than 50. {x x X and x < 50} = {5, 11, 15, 17, 21, 23, 27, 29, 33, 35, 39, 41, 45, 47} (b) Use induction to prove that every element of X is odd. Base case: 5 is odd. Assume that x X is odd, then x = 2k + 1 for some k Z both x + 6 = 2(k + 3) + 1 and 3x = 2(3k + 1) + 1 are odd, so all elements of X are odd. 9. Recall the definition for a sorted list: Definition An SList is B. x where x R, the real numbers. R. (X, Y ) where X and Y are SLists having the same number of elements, and the last number in X Page 3

4 is less than the first number in Y. Let L be an SList. Define a recursive function Dubup as follows. B. Suppose L = x. Then Dubup(L) = 2x+1. R. Suppose L = (X, Y ). Then Dubup(L) =Dubup(X)+Dubup(Y ). (a) Evaluate Dubup(((1, 2), (3, 4))), showing all steps. Dubup(((1, 2), (3, 4))) =Dubup((1, 2))+Dubup((3, 4)) =Dubup(1)+Dubup(2)+Dubup(3)+Dubup(4) = (2 + 1) + (4 + 1) + (6 + 1) + (8 + 1) = 24 (b) Give a recurrence relation for S(p), the number of + operations performed by Dubup on an SList of depth p, for p 0. { 1 : p = 0 S(p) = 2S(p 1) + 1 : p > 1 (c) Give a recurrence relation for M(p), the number of operations performed by Dubup on an SList of depth p, for p 0. { 1 : p = 0 M(p) = 2M(p 1) : p > Suppose that license plates in a certain municipality come in two forms: one digit (0... 9) followed by three letters (A... Z) followed by three digits. How many different license plates are possible? (You can express this as a product and not multiply it out.) = 175, 760, How many different strings can be formed by rearranging the letters of ABRACADABRA? (Again, express this as a product without multiplying.) 11! 5! 2 2 = The following figure consists of 6 horizontal lines and 12 vertical lines. The goal of this problem is to count the number of rectangles (squares are a kind of rectangle, but line segments are not). Let V be the set of all sets of two vertical lines, and let H be the set of all sets of two horizontal lines. Let R be the set of all rectangles in the figure. Define a function f : R V H by (a) Explain why f is well defined. Two vertical lines and two horizontal lines completely determine a rectangle in this scheme. Plus, all possible pairs of vertical and horizontal lines are in the domain. (b) Explain why f is one-to-one. The function f is 1-1 (injective) because two vertical and two horizontal lines determine a unique rectangle. Page 4

5 (c) Explain why f is onto. The function f is onto (surjective) because there is a rectangle for every two vertical and two horizontal lines: Every pair of vertical and horizontal lines is determined by some rectangle. (d) Compute R, the number of rectangles in the figure. ( 12 2 ) ( 6 2) = = 990. (e) The previous figure contains 6 12 = 72 intersection points. Let P be the set of all sets {X, Y } of two intersection points. Suppose we tried counting R by defining a function g : R P, which maps a rectangle to the set containing its lower left and upper right vertices: Explain why g is not a one-to-one correspondence. The function g is not onto (surjective): for example, if X is on the same vertical line as Y, there is no rectangle mapping to {X, Y }. 13. If you roll three four-sided dice (numbered 1,2,3, and 4), what is the probability of rolling a 5? There are 4 3 equally-likely outcomes. 113, 131, 311, 221, 212, 122 are the only ways to get a 5, so the probability is 6 64 = 3 = To verify this experimentally (empirically), run the Python 32 script: import random n=3 m= cnt = 0 for i in range(m): L = [ random. randrange(1,5) for i in range(n)] #p r i n t ( L ) if sum(l)==5: cnt += 1 print(cnt/m) which should, eventually (it s ten million iterations!) produce a result like Consider the following algorithm:: x 1 for i {1, 2, 3, 4} do for j {1, 2, 3, 4, 5} do x x + x for k {1, 2, 3, 4, 5, 6} do x x + 2 x x + 3 (a) Count the number of + operations done by this algorithm. The first nested for-loop executes 4 5 = 20 additions and the next executes = 48 additions, for a total of 68 additions. (b) What is the value of x after the algorithm finishes? It s easier to track the result of this algorithm by simplifying it first: x 1 Page 5

6 for i {1, 2, 3, 4} do for j {1, 2, 3, 4, 5} do x 2x x x + 30 The inner for-loop then is first doubling and then adding 30, five times: f(x) = 2(2(2(2(2x + 30) + 30) + 30) + 30) The first time through we get f(1) : , but then we loop it three more times: and again: , 015, 778, and finally: 1, 015, 778 2, 031, 586 4, 063, 202 8, 126, , 252, , 505, 826. There s a nice round number...perhaps a little Python script, to be sure: x=1 for i in range(4): print(i,x) for j in range(5): x = x+x for k in range(6): x += 5 x produces Out[14]: Let f : N R be a function. Then O(f) is the set of all functions g such that g(n) Kf(n) for some constant K > 0, and for all n N for some N > 0. If g O(f), we also say that g is big-oh of f. Let p, q N with 0 < p < q. Show that n p O(n q ) Choose K = 1 and N = 1, then g(n) = n p = nq n q p nq = f(n) since q p > 0 and n > Write a recursive function in pseudocode that computes the value of the following recurrence relation: { 1 : n = 1 T (n) = T (n 1) + n : n > 1 function T(n mathbbz) if n = 1 return 1 else return T (n 1) + n or, in Python, def T(n): if n == 1: return 1 else: Page 6

7 return T(n 1)+n for n in range(1,10): print( T(,n, )=,T(n)) T( 1 )= 1 T( 2 )= 3 T( 3 )= 6 T( 4 )= 10 T( 5 )= 15 T( 6 )= 21 T( 7 )= 28 T( 8 )= 36 T( 9 )= 45 The triangular numbers. 17. Let T be a binary tree shown below. (a) Suppose an algorithm uses a preorder traversal PreOrder(T, 17). What sequence of nodes would the algorithm traverse? I ll take advantage of some extra time and access to Python to do this. First, I enter the tree as a list like so: T = [21, #root [17, #left subtree [42,[], [19,[],[15,[],[]]]], [71, [16,[],[28,[],[]]], [91,[27,[],[]],[]]]], [13, #right subtree [11, [83,[],[87,[],[]]], [25,[14,[],[]],[]]], [82,[44,[97,[],[]],[]],[]]]] Then I run the Python code for preorder traversal that we wrote in class, including a print() statement for each visitation: def PreSearch(t,T): if len(t)==0: return False elif t==t[0]: Page 7

8 return True else: print(t[0],end=, ) return PreSearch(t,T[1]) or PreSearch(t,T[2]) print( PreSearch(88,T)) Here s the preorder traversal: 21,17,42,19,15,71,16,28,91,27,13,11,83,87,25,14,82,44,97 (b) Suppose the algorithm uses an inorder traversal InOrder(71, T ). What sequence of nodes would the algorithm traverse? Again, I ll use Python: def PostSearch(t,T): if len(t)==0: return False elif PostSearch(t,T[1]) or PostSearch(t,T[2]): return True else: print(t[0],end=, ) return t==t[0] print( PostSearch(71,T)) Returns 15,19,42,28,16,27,91,71,True 18. Is there an assignment of true/false values for the variables p, q, r, s, and t such that the formula [(p q) ( p r)] [(s t) ( s t)] takes the value true? If so, find such an assignment. If not, explain why not. Any assignment of values where p and q are both false will make the value of the formula true. The idea is that a false premis allows any conclusion at all. For example, If James Earl Ray shot MLK, then the cow jumps over the moon. Page 8

Math 15 - Spring Homework 5.2 Solutions

Math 15 - Spring Homework 5.2 Solutions Math 15 - Spring 2017 - Homework 5.2 Solutions 1. (5.2 # 14 (not assigned)) Use Prim s algorithm to construct a minimal spanning tree for the following network. Draw the minimal tree and compute its total

More information

CSE 332 Spring 2013: Midterm Exam (closed book, closed notes, no calculators)

CSE 332 Spring 2013: Midterm Exam (closed book, closed notes, no calculators) Name: Email address: Quiz Section: CSE 332 Spring 2013: Midterm Exam (closed book, closed notes, no calculators) Instructions: Read the directions for each question carefully before answering. We will

More information

CS134 Spring 2005 Final Exam Mon. June. 20, 2005 Signature: Question # Out Of Marks Marker Total

CS134 Spring 2005 Final Exam Mon. June. 20, 2005 Signature: Question # Out Of Marks Marker Total CS134 Spring 2005 Final Exam Mon. June. 20, 2005 Please check your tutorial (TUT) section from the list below: TUT 101: F 11:30, MC 4042 TUT 102: M 10:30, MC 4042 TUT 103: M 11:30, MC 4058 TUT 104: F 10:30,

More information

CSCI-401 Examlet #5. Name: Class: Date: True/False Indicate whether the sentence or statement is true or false.

CSCI-401 Examlet #5. Name: Class: Date: True/False Indicate whether the sentence or statement is true or false. Name: Class: Date: CSCI-401 Examlet #5 True/False Indicate whether the sentence or statement is true or false. 1. The root node of the standard binary tree can be drawn anywhere in the tree diagram. 2.

More information

Midterm CSE 21 Spring 2012

Midterm CSE 21 Spring 2012 Signature Name Student ID Midterm CSE 21 Spring 2012 Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 _ (20 points) _ (15 points) _ (13 points) _ (23 points) _ (10 points) _ (8 points) Total _ (89 points) (84

More information

CSE 373 Spring Midterm. Friday April 21st

CSE 373 Spring Midterm. Friday April 21st CSE 373 Spring 2006 Data Structures and Algorithms Midterm Friday April 21st NAME : Do all your work on these pages. Do not add any pages. Use back pages if necessary. Show your work to get partial credit.

More information

Algorithms and Data Structures

Algorithms and Data Structures Algorithms and Data Structures Spring 2019 Alexis Maciel Department of Computer Science Clarkson University Copyright c 2019 Alexis Maciel ii Contents 1 Analysis of Algorithms 1 1.1 Introduction.................................

More information

2.) From the set {A, B, C, D, E, F, G, H}, produce all of the four character combinations. Be sure that they are in lexicographic order.

2.) From the set {A, B, C, D, E, F, G, H}, produce all of the four character combinations. Be sure that they are in lexicographic order. Discrete Mathematics 2 - Test File - Spring 2013 Exam #1 1.) RSA - Suppose we choose p = 5 and q = 11. You're going to be sending the coded message M = 23. a.) Choose a value for e, satisfying the requirements

More information

CSE 332 Autumn 2013: Midterm Exam (closed book, closed notes, no calculators)

CSE 332 Autumn 2013: Midterm Exam (closed book, closed notes, no calculators) Name: Email address: Quiz Section: CSE 332 Autumn 2013: Midterm Exam (closed book, closed notes, no calculators) Instructions: Read the directions for each question carefully before answering. We will

More information

Midterm CSE 21 Fall 2012

Midterm CSE 21 Fall 2012 Signature Name Student ID Midterm CSE 21 Fall 2012 Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 _ (20 points) _ (15 points) _ (21 points) _ (13 points) _ (9 points) _ (7 points) Total _ (85 points) (80 points

More information

Multiple-choice (35 pt.)

Multiple-choice (35 pt.) CS 161 Practice Midterm I Summer 2018 Released: 7/21/18 Multiple-choice (35 pt.) 1. (2 pt.) Which of the following asymptotic bounds describe the function f(n) = n 3? The bounds do not necessarily need

More information

CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, CS1800 Discrete Structures Final

CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, CS1800 Discrete Structures Final CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, 2016 Instructions: CS1800 Discrete Structures Final 1. The exam is closed book and closed notes. You may

More information

CSE373: Data Structures and Algorithms Lecture 4: Asymptotic Analysis. Aaron Bauer Winter 2014

CSE373: Data Structures and Algorithms Lecture 4: Asymptotic Analysis. Aaron Bauer Winter 2014 CSE373: Data Structures and Algorithms Lecture 4: Asymptotic Analysis Aaron Bauer Winter 2014 Previously, on CSE 373 We want to analyze algorithms for efficiency (in time and space) And do so generally

More information

CS 3512, Spring Instructor: Doug Dunham. Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010

CS 3512, Spring Instructor: Doug Dunham. Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010 CS 3512, Spring 2011 Instructor: Doug Dunham Textbook: James L. Hein, Discrete Structures, Logic, and Computability, 3rd Ed. Jones and Barlett, 2010 Prerequisites: Calc I, CS2511 Rough course outline:

More information

1. Let n and m be positive integers with n m. a. Write the inclusion/exclusion formula for the number S(n, m) of surjections from {1, 2,...

1. Let n and m be positive integers with n m. a. Write the inclusion/exclusion formula for the number S(n, m) of surjections from {1, 2,... MATH 3012, Quiz 3, November 24, 2015, WTT Student Name and ID Number 1. Let n and m be positive integers with n m. a. Write the inclusion/exclusion formula for the number S(n, m) of surjections from {1,

More information

CS1800 Discrete Structures Final Version A

CS1800 Discrete Structures Final Version A CS1800 Discrete Structures Fall 2017 Profs. Aslam, Gold, & Pavlu December 11, 2017 CS1800 Discrete Structures Final Version A Instructions: 1. The exam is closed book and closed notes. You may not use

More information

Midterm solutions. n f 3 (n) = 3

Midterm solutions. n f 3 (n) = 3 Introduction to Computer Science 1, SE361 DGIST April 20, 2016 Professors Min-Soo Kim and Taesup Moon Midterm solutions Midterm solutions The midterm is a 1.5 hour exam (4:30pm 6:00pm). This is a closed

More information

Algorithm Analysis. (Algorithm Analysis ) Data Structures and Programming Spring / 48

Algorithm Analysis. (Algorithm Analysis ) Data Structures and Programming Spring / 48 Algorithm Analysis (Algorithm Analysis ) Data Structures and Programming Spring 2018 1 / 48 What is an Algorithm? An algorithm is a clearly specified set of instructions to be followed to solve a problem

More information

Faculty of Science FINAL EXAMINATION COMP-250 A Introduction to Computer Science School of Computer Science, McGill University

Faculty of Science FINAL EXAMINATION COMP-250 A Introduction to Computer Science School of Computer Science, McGill University NAME: STUDENT NUMBER:. Faculty of Science FINAL EXAMINATION COMP-250 A Introduction to Computer Science School of Computer Science, McGill University Examimer: Prof. Mathieu Blanchette December 8 th 2005,

More information

ASSIGNMENT 4 SOLUTIONS

ASSIGNMENT 4 SOLUTIONS MATH 71 ASSIGNMENT SOLUTIONS 1. If F : X X is a function, define f (x) to be (f f)(x), and inductively define f k (x) (f f k 1 )(x) for each integer k. (So f (x) (f f )(x) f(f(f(x))) for instance.) We

More information

U.C. Berkeley CS170 : Algorithms, Fall 2013 Midterm 1 Professor: Satish Rao October 10, Midterm 1 Solutions

U.C. Berkeley CS170 : Algorithms, Fall 2013 Midterm 1 Professor: Satish Rao October 10, Midterm 1 Solutions U.C. Berkeley CS170 : Algorithms, Fall 2013 Midterm 1 Professor: Satish Rao October 10, 2013 Midterm 1 Solutions 1 True/False 1. The Mayan base 20 system produces representations of size that is asymptotically

More information

UNIVERSITY OF CALIFORNIA, COLLEGE OF ENGINEERING E77N: INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS AND ENGINEERS

UNIVERSITY OF CALIFORNIA, COLLEGE OF ENGINEERING E77N: INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS AND ENGINEERS Page 1 of 14 UNIVERSITY OF CALIFORNIA, COLLEGE OF ENGINEERING E77N: INTRODUCTION TO COMPUTER PROGRAMMING FOR SCIENTISTS AND ENGINEERS Final Exam May 18, 2002 12:30 3:30 pm TOTAL 100 POINTS Notes: 1. Write

More information

Total Score /1 /20 /41 /15 /23 Grader

Total Score /1 /20 /41 /15 /23 Grader NAME: NETID: CS2110 Spring 2015 Prelim 2 April 21, 2013 at 5:30 0 1 2 3 4 Total Score /1 /20 /41 /15 /23 Grader There are 5 questions numbered 0..4 on 8 pages. Check now that you have all the pages. Write

More information

UCSD CSE 21, Spring 2014 [Section B00] Mathematics for Algorithm and System Analysis

UCSD CSE 21, Spring 2014 [Section B00] Mathematics for Algorithm and System Analysis UCSD CSE 21, Spring 2014 [Section B00] Mathematics for Algorithm and System Analysis Lecture 16 Class URL: http://vlsicad.ucsd.edu/courses/cse21-s14/ Lecture 16 Notes Goals for this week Graph basics Types

More information

Chapter 4. Divide-and-Conquer. Copyright 2007 Pearson Addison-Wesley. All rights reserved.

Chapter 4. Divide-and-Conquer. Copyright 2007 Pearson Addison-Wesley. All rights reserved. Chapter 4 Divide-and-Conquer Copyright 2007 Pearson Addison-Wesley. All rights reserved. Divide-and-Conquer The most-well known algorithm design strategy: 2. Divide instance of problem into two or more

More information

University of Toronto Department of Electrical and Computer Engineering. Midterm Examination. ECE 345 Algorithms and Data Structures Fall 2010

University of Toronto Department of Electrical and Computer Engineering. Midterm Examination. ECE 345 Algorithms and Data Structures Fall 2010 University of Toronto Department of Electrical and Computer Engineering Midterm Examination ECE 345 Algorithms and Data Structures Fall 2010 Print your name and ID number neatly in the space provided below;

More information

Assignment 1 (concept): Solutions

Assignment 1 (concept): Solutions CS10b Data Structures and Algorithms Due: Thursday, January 0th Assignment 1 (concept): Solutions Note, throughout Exercises 1 to 4, n denotes the input size of a problem. 1. (10%) Rank the following functions

More information

Recursive definition of sets and structural induction

Recursive definition of sets and structural induction CS2209A 2017 Applied Logic for Computer Science Lecture 21, 22 Recursive definition of sets and structural induction Instructor: Marc Moreno Maza 1 Tower of Hanoi game Rules of the game: Start with all

More information

CS 173 [A]: Discrete Structures, Fall 2012 Homework 8 Solutions

CS 173 [A]: Discrete Structures, Fall 2012 Homework 8 Solutions CS 173 [A]: Discrete Structures, Fall 01 Homework 8 Solutions This homework contains 4 problems worth a total of 35 points. It is due on Wednesday, November 14th, at 5pm. 1 Induction Proofs With Inequalities

More information

CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, CS1800 Discrete Structures Final

CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, CS1800 Discrete Structures Final CS1800 Discrete Structures Fall 2016 Profs. Aslam, Gold, Ossowski, Pavlu, & Sprague December 16, 2016 Instructions: CS1800 Discrete Structures Final 1. The exam is closed book and closed notes. You may

More information

Introduction to Algorithms May 14, 2003 Massachusetts Institute of Technology Professors Erik Demaine and Shafi Goldwasser.

Introduction to Algorithms May 14, 2003 Massachusetts Institute of Technology Professors Erik Demaine and Shafi Goldwasser. Introduction to Algorithms May 14, 2003 Massachusetts Institute of Technology 6.046J/18.410J Professors Erik Demaine and Shafi Goldwasser Practice Final Practice Final Do not open this exam booklet until

More information

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Summer I Instructions:

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Summer I Instructions: VIRG INIA POLYTECHNIC INSTITUTE AND STATE U T PROSI M UNI VERSI TY Instructions: Print your name in the space provided below. This examination is closed book and closed notes, aside from the permitted

More information

Friday Four Square! 4:15PM, Outside Gates

Friday Four Square! 4:15PM, Outside Gates Binary Search Trees Friday Four Square! 4:15PM, Outside Gates Implementing Set On Monday and Wednesday, we saw how to implement the Map and Lexicon, respectively. Let's now turn our attention to the Set.

More information

Complexity, Induction, and Recurrence Relations. CSE 373 Help Session 4/7/2016

Complexity, Induction, and Recurrence Relations. CSE 373 Help Session 4/7/2016 Complexity, Induction, and Recurrence Relations CSE 373 Help Session 4/7/2016 Big-O Definition Definition: g(n) is in O( f(n) ) if there exist positive constants c and n0 such that g(n) c f(n) for all

More information

CSC Design and Analysis of Algorithms. Lecture 6. Divide and Conquer Algorithm Design Technique. Divide-and-Conquer

CSC Design and Analysis of Algorithms. Lecture 6. Divide and Conquer Algorithm Design Technique. Divide-and-Conquer CSC 8301- Design and Analysis of Algorithms Lecture 6 Divide and Conuer Algorithm Design Techniue Divide-and-Conuer The most-well known algorithm design strategy: 1. Divide a problem instance into two

More information

CMPSCI 187: Programming With Data Structures. Lecture 5: Analysis of Algorithms Overview 16 September 2011

CMPSCI 187: Programming With Data Structures. Lecture 5: Analysis of Algorithms Overview 16 September 2011 CMPSCI 187: Programming With Data Structures Lecture 5: Analysis of Algorithms Overview 16 September 2011 Analysis of Algorithms Overview What is Analysis of Algorithms? L&C s Dishwashing Example Being

More information

CS 373: Combinatorial Algorithms, Spring 1999

CS 373: Combinatorial Algorithms, Spring 1999 CS 373: Combinatorial Algorithms, Spring 1999 Final Exam (May 7, 1999) Name: Net ID: Alias: This is a closed-book, closed-notes exam! If you brought anything with you besides writing instruments and your

More information

Assignment 1. Stefano Guerra. October 11, The following observation follows directly from the definition of in order and pre order traversal:

Assignment 1. Stefano Guerra. October 11, The following observation follows directly from the definition of in order and pre order traversal: Assignment 1 Stefano Guerra October 11, 2016 1 Problem 1 Describe a recursive algorithm to reconstruct an arbitrary binary tree, given its preorder and inorder node sequences as input. First, recall that

More information

Advanced Algorithm Design and Analysis (Lecture 12) SW5 fall 2005 Simonas Šaltenis E1-215b

Advanced Algorithm Design and Analysis (Lecture 12) SW5 fall 2005 Simonas Šaltenis E1-215b Advanced Algorithm Design and Analysis (Lecture 12) SW5 fall 2005 Simonas Šaltenis E1-215b simas@cs.aau.dk Range Searching in 2D Main goals of the lecture: to understand and to be able to analyze the kd-trees

More information

Exam 3 Practice Problems

Exam 3 Practice Problems Exam 3 Practice Problems HONOR CODE: You are allowed to work in groups on these problems, and also to talk to the TAs (the TAs have not seen these problems before and they do not know the solutions but

More information

1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1

1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1 Asymptotics, Recurrence and Basic Algorithms 1. [1 pt] What is the solution to the recurrence T(n) = 2T(n-1) + 1, T(1) = 1 1. O(logn) 2. O(n) 3. O(nlogn) 4. O(n 2 ) 5. O(2 n ) 2. [1 pt] What is the solution

More information

Solutions to Quiz 1. (a) (3 points) Vertices x and y are in the same connected component. Solution. P (x, y)

Solutions to Quiz 1. (a) (3 points) Vertices x and y are in the same connected component. Solution. P (x, y) Massachusetts Institute of Technology 6.042J/18.062J, Fall 05: Mathematics for Computer Science October 17 Prof. Albert R. Meyer and Prof. Ronitt Rubinfeld revised October 18, 2005, 125 minutes Solutions

More information

Assignment 8 CSCE 156/156H/RAIK 184H Spring 2017

Assignment 8 CSCE 156/156H/RAIK 184H Spring 2017 Assignment 8 CSCE 156/156H/RAIK 184H Spring 2017 Name(s) CSE Login Instructions Same partner/group policy as the project applies to this assignment. Answer each question as completely as possible. You

More information

Introduction to Computer Science and Programming for Astronomers

Introduction to Computer Science and Programming for Astronomers Introduction to Computer Science and Programming for Astronomers Lecture 3. István Szapudi Institute for Astronomy University of Hawaii January 24, 2018 Outline Reminder 1 Reminder 2 3 Where were we last

More information

Discrete Mathematics 2 Exam File Spring 2012

Discrete Mathematics 2 Exam File Spring 2012 Discrete Mathematics 2 Exam File Spring 2012 Exam #1 1.) Suppose f : X Y and A X. a.) Prove or disprove: f -1 (f(a)) A. Prove or disprove: A f -1 (f(a)). 2.) A die is rolled four times. What is the probability

More information

CS126 Final Exam Review

CS126 Final Exam Review CS126 Final Exam Review Fall 2007 1 Asymptotic Analysis (Big-O) Definition. f(n) is O(g(n)) if there exists constants c, n 0 > 0 such that f(n) c g(n) n n 0 We have not formed any theorems dealing with

More information

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring Instructions:

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring Instructions: VIRG INIA POLYTECHNIC INSTITUTE AND STATE U T PROSI M UNI VERSI TY Instructions: Print your name in the space provided below. This examination is closed book and closed notes, aside from the permitted

More information

Quiz 1 Solutions. (a) f(n) = n g(n) = log n Circle all that apply: f = O(g) f = Θ(g) f = Ω(g)

Quiz 1 Solutions. (a) f(n) = n g(n) = log n Circle all that apply: f = O(g) f = Θ(g) f = Ω(g) Introduction to Algorithms March 11, 2009 Massachusetts Institute of Technology 6.006 Spring 2009 Professors Sivan Toledo and Alan Edelman Quiz 1 Solutions Problem 1. Quiz 1 Solutions Asymptotic orders

More information

How much space does this routine use in the worst case for a given n? public static void use_space(int n) { int b; int [] A;

How much space does this routine use in the worst case for a given n? public static void use_space(int n) { int b; int [] A; How much space does this routine use in the worst case for a given n? public static void use_space(int n) { int b; int [] A; } if (n

More information

Lesson 10: Representing, Naming, and Evaluating Functions

Lesson 10: Representing, Naming, and Evaluating Functions : Representing, Naming, and Evaluation Functions Classwork Opening Exercise Study the 4 representations of a function below. How are these representations alike? How are they different? TABLE: Input 0

More information

CSC Design and Analysis of Algorithms

CSC Design and Analysis of Algorithms CSC 8301- Design and Analysis of Algorithms Lecture 6 Divide and Conquer Algorithm Design Technique Divide-and-Conquer The most-well known algorithm design strategy: 1. Divide a problem instance into two

More information

Module 07: Efficiency

Module 07: Efficiency Module 07: Efficiency Topics: Basic introduction to run-time efficiency Analyzing recursive code Analyzing iterative code 1 Consider the following two ways to calculate the maximum of a nonempty list.

More information

Solving Linear Recurrence Relations (8.2)

Solving Linear Recurrence Relations (8.2) EECS 203 Spring 2016 Lecture 18 Page 1 of 10 Review: Recurrence relations (Chapter 8) Last time we started in on recurrence relations. In computer science, one of the primary reasons we look at solving

More information

Divide-and-Conquer. Dr. Yingwu Zhu

Divide-and-Conquer. Dr. Yingwu Zhu Divide-and-Conquer Dr. Yingwu Zhu Divide-and-Conquer The most-well known algorithm design technique: 1. Divide instance of problem into two or more smaller instances 2. Solve smaller instances independently

More information

CSC Design and Analysis of Algorithms. Lecture 6. Divide and Conquer Algorithm Design Technique. Divide-and-Conquer

CSC Design and Analysis of Algorithms. Lecture 6. Divide and Conquer Algorithm Design Technique. Divide-and-Conquer CSC 8301- Design and Analysis of Algorithms Lecture 6 Divide and Conquer Algorithm Design Technique Divide-and-Conquer The most-well known algorithm design strategy: 1. Divide a problem instance into two

More information

CSE 332 Spring 2014: Midterm Exam (closed book, closed notes, no calculators)

CSE 332 Spring 2014: Midterm Exam (closed book, closed notes, no calculators) Name: Email address: Quiz Section: CSE 332 Spring 2014: Midterm Exam (closed book, closed notes, no calculators) Instructions: Read the directions for each question carefully before answering. We will

More information

TREES AND ORDERS OF GROWTH 7

TREES AND ORDERS OF GROWTH 7 TREES AND ORDERS OF GROWTH 7 COMPUTER SCIENCE 61A October 17, 2013 1 Trees In computer science, trees are recursive data structures that are widely used in various settings. This is a diagram of a simple

More information

CS521 \ Notes for the Final Exam

CS521 \ Notes for the Final Exam CS521 \ Notes for final exam 1 Ariel Stolerman Asymptotic Notations: CS521 \ Notes for the Final Exam Notation Definition Limit Big-O ( ) Small-o ( ) Big- ( ) Small- ( ) Big- ( ) Notes: ( ) ( ) ( ) ( )

More information

Indicate the option which most accurately completes the sentence.

Indicate the option which most accurately completes the sentence. Discrete Structures, CSCI 246, Fall 2015 Final, Dec. 10 Indicate the option which most accurately completes the sentence. 1. Say that Discrete(x) means that x is a discrete structures exam and Well(x)

More information

Basic Properties The Definition of Catalan Numbers

Basic Properties The Definition of Catalan Numbers 1 Basic Properties 1.1. The Definition of Catalan Numbers There are many equivalent ways to define Catalan numbers. In fact, the main focus of this monograph is the myriad combinatorial interpretations

More information

Divide-and-Conquer. The most-well known algorithm design strategy: smaller instances. combining these solutions

Divide-and-Conquer. The most-well known algorithm design strategy: smaller instances. combining these solutions Divide-and-Conquer The most-well known algorithm design strategy: 1. Divide instance of problem into two or more smaller instances 2. Solve smaller instances recursively 3. Obtain solution to original

More information

CS302 Topic: Algorithm Analysis #2. Thursday, Sept. 21, 2006

CS302 Topic: Algorithm Analysis #2. Thursday, Sept. 21, 2006 CS302 Topic: Algorithm Analysis #2 Thursday, Sept. 21, 2006 Analysis of Algorithms The theoretical study of computer program performance and resource usage What s also important (besides performance/resource

More information

CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims. Lecture 10: Asymptotic Complexity and

CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims. Lecture 10: Asymptotic Complexity and CS/ENGRD 2110 Object-Oriented Programming and Data Structures Spring 2012 Thorsten Joachims Lecture 10: Asymptotic Complexity and What Makes a Good Algorithm? Suppose you have two possible algorithms or

More information

PROGRAM EFFICIENCY & COMPLEXITY ANALYSIS

PROGRAM EFFICIENCY & COMPLEXITY ANALYSIS Lecture 03-04 PROGRAM EFFICIENCY & COMPLEXITY ANALYSIS By: Dr. Zahoor Jan 1 ALGORITHM DEFINITION A finite set of statements that guarantees an optimal solution in finite interval of time 2 GOOD ALGORITHMS?

More information

Name CPTR246 Spring '17 (100 total points) Exam 3

Name CPTR246 Spring '17 (100 total points) Exam 3 Name CPTR246 Spring '17 (100 total points) Exam 3 1. Linked Lists Consider the following linked list of integers (sorted from lowest to highest) and the changes described. Make the necessary changes in

More information

10/5/2016. Comparing Algorithms. Analyzing Code ( worst case ) Example. Analyzing Code. Binary Search. Linear Search

10/5/2016. Comparing Algorithms. Analyzing Code ( worst case ) Example. Analyzing Code. Binary Search. Linear Search 10/5/2016 CSE373: Data Structures and Algorithms Asymptotic Analysis (Big O,, and ) Steve Tanimoto Autumn 2016 This lecture material represents the work of multiple instructors at the University of Washington.

More information

Math 187 Sample Test II Questions

Math 187 Sample Test II Questions Math 187 Sample Test II Questions Dr. Holmes October 2, 2008 These are sample questions of kinds which might appear on Test II. There is no guarantee that all questions on the test will look like these!

More information

Chapter 1 Programming: A General Overview

Chapter 1 Programming: A General Overview Chapter 1 Programming: A General Overview 2 Introduction This class is an introduction to the design, implementation, and analysis of algorithms. Examples: sorting large amounts of data organizing information

More information

INF2220: algorithms and data structures Series 1

INF2220: algorithms and data structures Series 1 Universitetet i Oslo Institutt for Informatikk I. Yu, D. Karabeg INF2220: algorithms and data structures Series 1 Topic Function growth & estimation of running time, trees Issued: 24. 08. 2016 Exercise

More information

Question 7.11 Show how heapsort processes the input:

Question 7.11 Show how heapsort processes the input: Question 7.11 Show how heapsort processes the input: 142, 543, 123, 65, 453, 879, 572, 434, 111, 242, 811, 102. Solution. Step 1 Build the heap. 1.1 Place all the data into a complete binary tree in the

More information

Solutions to the Second Midterm Exam

Solutions to the Second Midterm Exam CS/Math 240: Intro to Discrete Math 3/27/2011 Instructor: Dieter van Melkebeek Solutions to the Second Midterm Exam Problem 1 This question deals with the following implementation of binary search. Function

More information

SEARCHING, SORTING, AND ASYMPTOTIC COMPLEXITY. Lecture 11 CS2110 Spring 2016

SEARCHING, SORTING, AND ASYMPTOTIC COMPLEXITY. Lecture 11 CS2110 Spring 2016 1 SEARCHING, SORTING, AND ASYMPTOTIC COMPLEXITY Lecture 11 CS2110 Spring 2016 Time spent on A2 2 Histogram: [inclusive:exclusive) [0:1): 0 [1:2): 24 ***** [2:3): 84 ***************** [3:4): 123 *************************

More information

CIS 121 Data Structures and Algorithms Midterm 3 Review Solution Sketches Fall 2018

CIS 121 Data Structures and Algorithms Midterm 3 Review Solution Sketches Fall 2018 CIS 121 Data Structures and Algorithms Midterm 3 Review Solution Sketches Fall 2018 Q1: Prove or disprove: You are given a connected undirected graph G = (V, E) with a weight function w defined over its

More information

Computer Science E-22 Practice Final Exam

Computer Science E-22 Practice Final Exam name Computer Science E-22 This exam consists of three parts. Part I has 10 multiple-choice questions that you must complete. Part II consists of 4 multi-part problems, of which you must complete 3, and

More information

In addition to the correct answer, you MUST show all your work in order to receive full credit.

In addition to the correct answer, you MUST show all your work in order to receive full credit. In addition to the correct answer, you MUST show all your work in order to receive full credit. Questions Mark: Question1) Multiple Choice Questions /10 Question 2) Binary Trees /15 Question 3) Linked

More information

CS1800 Discrete Structures Final Version B

CS1800 Discrete Structures Final Version B CS1800 Discrete Structures Fall 2017 Profs. Aslam, Gold, & Pavlu December 15, 2017 CS1800 Discrete Structures Final Version B Instructions: 1. The exam is closed book and closed notes. You may not use

More information

Prelim 2. CS 2110, November 20, 2014, 7:30 PM Extra Total Question True/False Short Answer

Prelim 2. CS 2110, November 20, 2014, 7:30 PM Extra Total Question True/False Short Answer Prelim 2 CS 2110, November 20, 2014, 7:30 PM 1 2 3 4 5 Extra Total Question True/False Short Answer Complexity Induction Trees Graphs Extra Credit Max 20 10 15 25 30 5 100 Score Grader The exam is closed

More information

1 Format. 2 Topics Covered. 2.1 Minimal Spanning Trees. 2.2 Union Find. 2.3 Greedy. CS 124 Quiz 2 Review 3/25/18

1 Format. 2 Topics Covered. 2.1 Minimal Spanning Trees. 2.2 Union Find. 2.3 Greedy. CS 124 Quiz 2 Review 3/25/18 CS 124 Quiz 2 Review 3/25/18 1 Format You will have 83 minutes to complete the exam. The exam may have true/false questions, multiple choice, example/counterexample problems, run-this-algorithm problems,

More information

I. Recursive Descriptions A phrase like to get the next term you add 2, which tells how to obtain

I. Recursive Descriptions A phrase like to get the next term you add 2, which tells how to obtain Mathematics 45 Describing Patterns in s Mathematics has been characterized as the science of patterns. From an early age students see patterns in mathematics, including counting by twos, threes, etc.,

More information

CS1110 Lab 6 (Mar 17-18, 2015)

CS1110 Lab 6 (Mar 17-18, 2015) CS1110 Lab 6 (Mar 17-18, 2015) First Name: Last Name: NetID: The lab assignments are very important and you must have a CS 1110 course consultant tell CMS that you did the work. (Correctness does not matter.)

More information

Prelim 2, CS2110. SOLUTION

Prelim 2, CS2110. SOLUTION Prelim 2, CS2110. SOLUTION 7:30 PM, 25 April 2017 1. Name (1 point) Write your name and NetID at the top of every page of this exam. 2. Short Answer (26 points.) (a) Asymptotic complexity. 8 points. Be

More information

University of Waterloo Department of Electrical and Computer Engineering ECE 250 Data Structures and Algorithms. Final Examination T09:00

University of Waterloo Department of Electrical and Computer Engineering ECE 250 Data Structures and Algorithms. Final Examination T09:00 University of Waterloo Department of Electrical and Computer Engineering ECE 250 Data Structures and Algorithms Instructor: Douglas Wilhelm Harder Time: 2.5 hours Aides: none 18 pages Final Examination

More information

Computer Science Foundation Exam

Computer Science Foundation Exam Computer Science Foundation Exam August 6, 017 Section I A DATA STRUCTURES SOLUTIONS NO books, notes, or calculators may be used, and you must work entirely on your own. Question # Max Pts Category Passing

More information

(b) int count = 0; int i = 1; while (i<m) { for (int j=i; j<n; j++) { count = count + 1; i = i + 1; O(M + N 2 ) (c) int count = 0; int i,j,k; for (i=1

(b) int count = 0; int i = 1; while (i<m) { for (int j=i; j<n; j++) { count = count + 1; i = i + 1; O(M + N 2 ) (c) int count = 0; int i,j,k; for (i=1 CPS 100 Exam 2 Solutions Spring 199 Dr Rodger 1 (3 pts) A virtual function in C++ is bound dynamically or statically? dynamic 2 (3 pts) When does one use a class template in C++? Templates are used to

More information

Notation Index. Probability notation. (there exists) (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5.

Notation Index. Probability notation. (there exists) (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5. Notation Index (there exists) (for all) Fn-4 Fn-4 (such that) Fn-4 B n (Bell numbers) CL-27 s t (equivalence relation) GT-5 ( n ) k (binomial coefficient) CL-15 ( n m 1,m 2,...) (multinomial coefficient)

More information

CSE 373 Spring 2010: Midterm #1 (closed book, closed notes, NO calculators allowed)

CSE 373 Spring 2010: Midterm #1 (closed book, closed notes, NO calculators allowed) Name: Email address: CSE 373 Spring 2010: Midterm #1 (closed book, closed notes, NO calculators allowed) Instructions: Read the directions for each question carefully before answering. We may give partial

More information

Algebra 2 Semester 1 (#2221)

Algebra 2 Semester 1 (#2221) Instructional Materials for WCSD Math Common Finals The Instructional Materials are for student and teacher use and are aligned to the 2016-2017 Course Guides for the following course: Algebra 2 Semester

More information

CMPSCI 311: Introduction to Algorithms Practice Final Exam

CMPSCI 311: Introduction to Algorithms Practice Final Exam CMPSCI 311: Introduction to Algorithms Practice Final Exam Name: ID: Instructions: Answer the questions directly on the exam pages. Show all your work for each question. Providing more detail including

More information

9/10/2018 Algorithms & Data Structures Analysis of Algorithms. Siyuan Jiang, Sept

9/10/2018 Algorithms & Data Structures Analysis of Algorithms. Siyuan Jiang, Sept 9/10/2018 Algorithms & Data Structures Analysis of Algorithms Siyuan Jiang, Sept. 2018 1 Email me if the office door is closed Siyuan Jiang, Sept. 2018 2 Grades have been emailed github.com/cosc311/assignment01-userid

More information

NANYANG TECHNOLOGICAL UNIVERSITY SEMESTER II EXAMINATION MH 1301 DISCRETE MATHEMATICS TIME ALLOWED: 2 HOURS

NANYANG TECHNOLOGICAL UNIVERSITY SEMESTER II EXAMINATION MH 1301 DISCRETE MATHEMATICS TIME ALLOWED: 2 HOURS NANYANG TECHNOLOGICAL UNIVERSITY SEMESTER II EXAMINATION 2015-2016 MH 1301 DISCRETE MATHEMATICS May 2016 TIME ALLOWED: 2 HOURS INSTRUCTIONS TO CANDIDATES 1. This examination paper contains FIVE (5) questions

More information

Lesson 20: Every Line is a Graph of a Linear Equation

Lesson 20: Every Line is a Graph of a Linear Equation Student Outcomes Students know that any non vertical line is the graph of a linear equation in the form of, where is a constant. Students write the equation that represents the graph of a line. Lesson

More information

CSE 2320 Section 002, Fall 2015 Exam 2 Time: 80 mins

CSE 2320 Section 002, Fall 2015 Exam 2 Time: 80 mins CSE 2320 Section 002, Fall 201 Exam 2 Time: 80 mins Name:. Student ID:. Total exam points: 100. Question Points Out of 1 24 2 10 3 10 4 18 6 1 16 Total 100 If you have the smallest doubt about what a question

More information

Design and Analysis of Algorithms - - Assessment

Design and Analysis of Algorithms - - Assessment X Courses» Design and Analysis of Algorithms Week 1 Quiz 1) In the code fragment below, start and end are integer values and prime(x) is a function that returns true if x is a prime number and false otherwise.

More information

CPS 616 TRANSFORM-AND-CONQUER 7-1

CPS 616 TRANSFORM-AND-CONQUER 7-1 CPS 616 TRANSFORM-AND-CONQUER 7-1 TRANSFORM AND CONQUER Group of techniques to solve a problem by first transforming the problem into one of: 1. a simpler/more convenient instance of the same problem (instance

More information

Notation Index 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coef

Notation Index 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coef Notation 9 (there exists) Fn-4 8 (for all) Fn-4 3 (such that) Fn-4 B n (Bell numbers) CL-25 s ο t (equivalence relation) GT-4 n k (binomial coefficient) CL-14 (multinomial coefficient) CL-18 n m 1 ;m 2

More information

Fast algorithm for generating ascending compositions

Fast algorithm for generating ascending compositions manuscript No. (will be inserted by the editor) Fast algorithm for generating ascending compositions Mircea Merca Received: date / Accepted: date Abstract In this paper we give a fast algorithm to generate

More information

You should know the first sum above. The rest will be given if you ever need them. However, you should remember that,, and.

You should know the first sum above. The rest will be given if you ever need them. However, you should remember that,, and. Big-Oh Notation Formal Definitions A function is in (upper bound) iff there exist positive constants k and n 0 such that for all. A function is in (lower bound) iff there exist positive constants k and

More information

Recursion defining an object (or function, algorithm, etc.) in terms of itself. Recursion can be used to define sequences

Recursion defining an object (or function, algorithm, etc.) in terms of itself. Recursion can be used to define sequences Section 5.3 1 Recursion 2 Recursion Recursion defining an object (or function, algorithm, etc.) in terms of itself. Recursion can be used to define sequences Previously sequences were defined using a specific

More information

Spring 2017 CS 1110/1111 Exam 2

Spring 2017 CS 1110/1111 Exam 2 Spring 2017 CS 1110/1111 Exam 2 Bubble in your computing ID in the footer of this page. We use an optical scanner to read it, so fill in the bubbles darkly. If you have a shorter ID, leave some rows blank.

More information

COMP 250 Fall recurrences 2 Oct. 13, 2017

COMP 250 Fall recurrences 2 Oct. 13, 2017 COMP 250 Fall 2017 15 - recurrences 2 Oct. 13, 2017 Here we examine the recurrences for mergesort and quicksort. Mergesort Recall the mergesort algorithm: we divide the list of things to be sorted into

More information